Integrated control of electric vehicles based on active front steering and model predictive control

• Published in: Control engineering practice Vol. 121; p. 105066
• Main Authors: Jing, ChangQing, Shu, HongYu, Shu, Ran, Song, Yitong
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.04.2022
• Subjects: Active Front Steering; Distributed drive electric vehicles; Energy savings; Model Predictive Control; Torque distribution; Vehicle stability; Vehicle stability; Torque distribution; Model Predictive Control; Distributed drive electric vehicles; Energy savings; Active Front Steering
• ISSN: 0967-0661; 1873-6939
• DOI: 10.1016/j.conengprac.2022.105066

Energy efficiency and handling stability are of the most importance for the control of electric vehicles. It is a challenge to maintain the stability and mobility of the vehicle at the cost of minimum energy under various driving conditions. A novel integrated control strategy of yaw stability and energy efficiency based on model predictive control and active steering system is presented. To improve the energy efficiency of the in-wheel motors, a global search algorithm of the instantaneous optimal efficiency of the motor is used to obtain the optimal torque distribution of the front and rear axles. Meanwhile, a terminal sliding mode controller is presented to maintain the lateral stability of the vehicle under general conditions. To reduce the large additional yaw moment of the vehicle under high-speed cornering condition, the model predictive controller is used to coordinate the active steering system and the direct yaw moment control system. Then, to balance the lateral stability and energy efficiency of the vehicle under extreme conditions, a stability judgment controller is proposed, which based on the theory of phase plane and yaw rate threshold method. The simulation results show that the integrated control strategy can improve the lateral stability of the vehicle under different road friction conditions, and compared with the control strategy without motor efficiency optimization , the integrated control strategy reduces the energy consumption by 21.66% and 11.18% in the ‘sine steering’ and ‘single lane change’ maneuver, respectively. In the slalom maneuver, the energy consumption of the integrated control strategy with energy saving optimization function is reduced by 10.13%. •An off-line global search optimization algorithm based on motor efficiency map is proposed.•A scheme of coordinated control of AFS and DYC by LTV-MPC controller is proposed.•Based on phase plane theory and yaw rate threshold method, a stability judgment controller is proposed.